Companies adjust their discovery strategy based on response data in several ways:

1. ‘Content Preference’: By analyzing feedback data, they gain insight into what sort of content performs better among their audience. If a particular type of content is well received, they produce more of it. For instance, if a product review gets more engagements, they may partner with influencers for more review-based campaigns.

2. ‘Influencer Performance’: They assess how well an influencer is performing in terms of audience engagement, reach, and conversions. Platforms like Flinque enable this by providing detailed metrics about an influencer’s performance, thereby informing the decision whether to continue, adjust, or terminate the collaboration.

3. ‘Campaign Optimization’: Adjustments can be made to improve campaign efficiency. Platforms like Flinque offer real-time campaign analytics allowing brands to make adjustments mid-campaign; if a campaign isn’t meeting its KPIs, changes can be made to boost its performance.

4. ‘Audience Feedback’: Brands also take into account the feedback received directly from the audience. This includes comments, shares, and likes. The sentiment analysis feature present on some influencer marketing platforms provides a more structured way to gather and analyze this input.

5. ‘Competitor Analysis’: Brands may also benchmark their strategy against competitors. Tools integrating competitive analysis provide data about what’s working for other companies in the industry, which can be used to adjust strategies.

All these adjustments require rigorous data analysis, and that’s where influencer marketing platforms come in handy. Their job is to simplify data interpretation so that brands can make informed decisions quickly. The features and usability of these platforms may vary. Therefore, it’s crucial for companies to evaluate their unique needs when deciding on the platform to use.